Cerebellum

Seed-based functional connectivity of the cerebellum (9 ROI)

MIST 64 parcellation: https://simexp.github.io/multiscale_dashboard/index.html
Color scales represents beta values per region (eg. synchronisation of the activity of the vermis part to the rest of the brain (=n=63 regions) in patients with ASD vs Controls).
Cov: age, mean connectivity, scanning site, motion, sex
In [ ]:
import pandas as pd
import nibabel as nib
import pathlib as pal
from nilearn import plotting #Abraham, A. et al. Machine learning for neuroimaging with scikit-learn. Front. Neuroinform. 8, 14 (2014).
from nilearn import input_data as nii
from nilearn import plotting as nlp 
from matplotlib import pyplot as plt
import nilearn.plotting as nip
from niwidgets import NiftiWidget ## https://github.com/nipy/niwidgets
from IPython.display import Image, display
In [8]:
mist_64_p = '/Users/Clara/Desktop/MIST/Parcellations/MIST_64.nii.gz'
labels_p = '/Users/Clara/Desktop/MIST/Parcel_Information/MIST_64.csv'
mist64_i = nib.load(mist_64_p)
mist64 = mist64_i.get_data()
labels = pd.read_csv(labels_p, delimiter=';')
mask = mist64_i.get_data().astype(bool)
root_p = pal.Path('/Users/Clara/Desktop/DiGregorio').resolve()
mask_i = nib.Nifti1Image(mask, affine=mist64_i.affine, header=mist64_i.header)
masker = nii.NiftiMasker(mask_img=mask_i, standardize=False)
masker.fit()
atlas_vec = masker.fit_transform(mist64_i).squeeze() - 1
In [4]:
display(Image(filename='/Users/Clara/Desktop/DiGregorio/atlas_cereb.png'))
#MIST64 = NiftiWidget('/Users/Clara/Desktop/MIST/Parcellations/MIST_64.nii.gz')
#MIST64.nifti_plotter()
#MIST64.nifti_plotter(plotting_func=nip.plot_glass_brain)

CEREBELLUM VERMIS

In [12]:
COND_p = root_p / 'CERVM_seed_minibrain.csv'
COND=pd.read_csv(COND_p, sep=',')
In [13]:
COND_brain_vec = COND.ASD[atlas_vec]
COND_brain_img = masker.inverse_transform(COND_brain_vec)

nlp.view_img(COND_brain_img, title="ASD CERVM", cmap=plt.cm.seismic, vmax=0.5, threshold=0.1)
Out[13]:
In [6]:
COND_brain_vec = COND.SZ[atlas_vec]
COND_brain_img = masker.inverse_transform(COND_brain_vec)

nlp.view_img(COND_brain_img, title="SZ CERVM", cmap=plt.cm.seismic, vmax=0.5, threshold=0.2)
Out[6]:
In [7]:
COND_brain_vec = COND.BIP[atlas_vec]
COND_brain_img = masker.inverse_transform(COND_brain_vec)

nlp.view_img(COND_brain_img, title="Bipolar CERVM", cmap=plt.cm.seismic, vmax=0.5, threshold=0.2)
Out[7]:

Cereb I-V Biventral Lobule

In [8]:
COND_p = root_p / 'CER5_seed_minibrain.csv'
COND=pd.read_csv(COND_p, sep=',')
In [9]:
COND_brain_vec = COND.ASD[atlas_vec]
COND_brain_img = masker.inverse_transform(COND_brain_vec)

nlp.view_img(COND_brain_img, title="ASD CER5", cmap=plt.cm.seismic, vmax=0.5, threshold=0.1)
Out[9]:
In [10]:
COND_brain_vec = COND.SZ[atlas_vec]
COND_brain_img = masker.inverse_transform(COND_brain_vec)

nlp.view_img(COND_brain_img, title="SZ CER5", cmap=plt.cm.seismic, vmax=0.5, threshold=0.2)
Out[10]:
In [11]:
COND_brain_vec = COND.BIP[atlas_vec]
COND_brain_img = masker.inverse_transform(COND_brain_vec)

nlp.view_img(COND_brain_img, title="BIP CER5", cmap=plt.cm.seismic, vmax=0.5, threshold=0.2)
Out[11]:

CEREBELLUM_VI

In [12]:
COND_p = root_p / 'CER6_seed_minibrain.csv'
COND=pd.read_csv(COND_p, sep=',')
In [13]:
COND_brain_vec = COND.ASD[atlas_vec]
COND_brain_img = masker.inverse_transform(COND_brain_vec)

nlp.view_img(COND_brain_img, title="ASD CER6", cmap=plt.cm.seismic, vmax=0.5, threshold=0.1)
Out[13]:
In [14]:
COND_brain_vec = COND.SZ[atlas_vec]
COND_brain_img = masker.inverse_transform(COND_brain_vec)

nlp.view_img(COND_brain_img, title="SZ CER6", cmap=plt.cm.seismic, vmax=0.5, threshold=0.2)
Out[14]:
In [15]:
COND_brain_vec = COND.BIP[atlas_vec]
COND_brain_img = masker.inverse_transform(COND_brain_vec)

nlp.view_img(COND_brain_img, title="BIP CER6", cmap=plt.cm.seismic, vmax=0.5, threshold=0.2)
Out[15]:

CEREBELLUM_VIIIab

In [16]:
COND_p = root_p / 'CER7ab_seed_minibrain.csv'
COND=pd.read_csv(COND_p, sep=',')
In [17]:
COND_brain_vec = COND.ASD[atlas_vec]
COND_brain_img = masker.inverse_transform(COND_brain_vec)

nlp.view_img(COND_brain_img, title="ASD CER7ab", cmap=plt.cm.seismic, vmax=0.5, threshold=0.1)

/Users/Clara/anaconda3/lib/python3.6/site-packages/nilearn/reporting/html_document.py:60: UserWarning: It seems you have created more than 10 nilearn views. As each view uses dozens of megabytes of RAM, you might want to delete some of them.
  MAX_IMG_VIEWS_BEFORE_WARNING))
Out[17]:
In [18]:
COND_brain_vec = COND.SZ[atlas_vec]
COND_brain_img = masker.inverse_transform(COND_brain_vec)

nlp.view_img(COND_brain_img, title="SZ CER7ab", cmap=plt.cm.seismic, vmax=0.5, threshold=0.1)

/Users/Clara/anaconda3/lib/python3.6/site-packages/nilearn/reporting/html_document.py:60: UserWarning: It seems you have created more than 10 nilearn views. As each view uses dozens of megabytes of RAM, you might want to delete some of them.
  MAX_IMG_VIEWS_BEFORE_WARNING))
Out[18]:
In [19]:
COND_brain_vec = COND.BIP[atlas_vec]
COND_brain_img = masker.inverse_transform(COND_brain_vec)

nlp.view_img(COND_brain_img, title="BIP CER7ab", cmap=plt.cm.seismic, vmax=0.5, threshold=0.2)

/Users/Clara/anaconda3/lib/python3.6/site-packages/nilearn/reporting/html_document.py:60: UserWarning: It seems you have created more than 10 nilearn views. As each view uses dozens of megabytes of RAM, you might want to delete some of them.
  MAX_IMG_VIEWS_BEFORE_WARNING))
Out[19]:

CEREBELLUM_VIIb

In [20]:
COND_p = root_p / 'CER7b_seed_minibrain.csv'
COND=pd.read_csv(COND_p, sep=',')
In [21]:
COND_brain_vec = COND.ASD[atlas_vec]
COND_brain_img = masker.inverse_transform(COND_brain_vec)

nlp.view_img(COND_brain_img, title="ASD CER7b", cmap=plt.cm.seismic, vmax=0.5, threshold=0.1)

/Users/Clara/anaconda3/lib/python3.6/site-packages/nilearn/reporting/html_document.py:60: UserWarning: It seems you have created more than 10 nilearn views. As each view uses dozens of megabytes of RAM, you might want to delete some of them.
  MAX_IMG_VIEWS_BEFORE_WARNING))
Out[21]:
In [22]:
COND_brain_vec = COND.SZ[atlas_vec]
COND_brain_img = masker.inverse_transform(COND_brain_vec)

nlp.view_img(COND_brain_img, title="SZ CER7b", cmap=plt.cm.seismic, vmax=0.5, threshold=0.1)

/Users/Clara/anaconda3/lib/python3.6/site-packages/nilearn/reporting/html_document.py:60: UserWarning: It seems you have created more than 10 nilearn views. As each view uses dozens of megabytes of RAM, you might want to delete some of them.
  MAX_IMG_VIEWS_BEFORE_WARNING))
Out[22]:
In [23]:
COND_brain_vec = COND.BIP[atlas_vec]
COND_brain_img = masker.inverse_transform(COND_brain_vec)

nlp.view_img(COND_brain_img, title="BIP CER7b", cmap=plt.cm.seismic, vmax=0.5, threshold=0.1)

/Users/Clara/anaconda3/lib/python3.6/site-packages/nilearn/reporting/html_document.py:60: UserWarning: It seems you have created more than 10 nilearn views. As each view uses dozens of megabytes of RAM, you might want to delete some of them.
  MAX_IMG_VIEWS_BEFORE_WARNING))
Out[23]:

CEREBELLUM IX

In [24]:
COND_p = root_p / 'CER9_seed_minibrain.csv'
COND=pd.read_csv(COND_p, sep=',')
In [25]:
COND_brain_vec = COND.ASD[atlas_vec]
COND_brain_img = masker.inverse_transform(COND_brain_vec)

nlp.view_img(COND_brain_img, title="ASD CER IX", cmap=plt.cm.seismic, vmax=0.5, threshold=0.1)

/Users/Clara/anaconda3/lib/python3.6/site-packages/nilearn/reporting/html_document.py:60: UserWarning: It seems you have created more than 10 nilearn views. As each view uses dozens of megabytes of RAM, you might want to delete some of them.
  MAX_IMG_VIEWS_BEFORE_WARNING))
Out[25]:
In [26]:
COND_brain_vec = COND.SZ[atlas_vec]
COND_brain_img = masker.inverse_transform(COND_brain_vec)

nlp.view_img(COND_brain_img, title="SZ CER IX", cmap=plt.cm.seismic, vmax=0.5, threshold=0.1)

/Users/Clara/anaconda3/lib/python3.6/site-packages/nilearn/reporting/html_document.py:60: UserWarning: It seems you have created more than 10 nilearn views. As each view uses dozens of megabytes of RAM, you might want to delete some of them.
  MAX_IMG_VIEWS_BEFORE_WARNING))
Out[26]:
In [27]:
COND_brain_vec = COND.BIP[atlas_vec]
COND_brain_img = masker.inverse_transform(COND_brain_vec)

nlp.view_img(COND_brain_img, title="BIP CER IX", cmap=plt.cm.seismic, vmax=0.5, threshold=0.1)

/Users/Clara/anaconda3/lib/python3.6/site-packages/nilearn/reporting/html_document.py:60: UserWarning: It seems you have created more than 10 nilearn views. As each view uses dozens of megabytes of RAM, you might want to delete some of them.
  MAX_IMG_VIEWS_BEFORE_WARNING))
Out[27]:

CEREBELLUM_CRUSI

In [28]:
COND_p = root_p / 'CERCR1_seed_minibrain.csv'
COND=pd.read_csv(COND_p, sep=',')
In [29]:
COND_brain_vec = COND.ASD[atlas_vec]
COND_brain_img = masker.inverse_transform(COND_brain_vec)

nlp.view_img(COND_brain_img, title="ASD CER CRUS I", cmap=plt.cm.seismic, vmax=0.5, threshold=0.1)

/Users/Clara/anaconda3/lib/python3.6/site-packages/nilearn/reporting/html_document.py:60: UserWarning: It seems you have created more than 10 nilearn views. As each view uses dozens of megabytes of RAM, you might want to delete some of them.
  MAX_IMG_VIEWS_BEFORE_WARNING))
Out[29]:
In [30]:
COND_brain_vec = COND.SZ[atlas_vec]
COND_brain_img = masker.inverse_transform(COND_brain_vec)

nlp.view_img(COND_brain_img, title="SZ CER CRUS I", cmap=plt.cm.seismic, vmax=0.5, threshold=0.1)

/Users/Clara/anaconda3/lib/python3.6/site-packages/nilearn/reporting/html_document.py:60: UserWarning: It seems you have created more than 10 nilearn views. As each view uses dozens of megabytes of RAM, you might want to delete some of them.
  MAX_IMG_VIEWS_BEFORE_WARNING))
Out[30]:
In [31]:
COND_brain_vec = COND.BIP[atlas_vec]
COND_brain_img = masker.inverse_transform(COND_brain_vec)

nlp.view_img(COND_brain_img, title="BIP CER CRUS I", cmap=plt.cm.seismic, vmax=0.5, threshold=0.1)

/Users/Clara/anaconda3/lib/python3.6/site-packages/nilearn/reporting/html_document.py:60: UserWarning: It seems you have created more than 10 nilearn views. As each view uses dozens of megabytes of RAM, you might want to delete some of them.
  MAX_IMG_VIEWS_BEFORE_WARNING))
Out[31]:

CRUS 2 - Left

In [32]:
COND_p = root_p / 'L_CERCR2_seed_minibrain.csv'
COND=pd.read_csv(COND_p, sep=',')
In [33]:
COND_brain_vec = COND.ASD[atlas_vec]
COND_brain_img = masker.inverse_transform(COND_brain_vec)

nlp.view_img(COND_brain_img, title="ASD CER CRUS II L", cmap=plt.cm.seismic, vmax=0.5, threshold=0.1)

/Users/Clara/anaconda3/lib/python3.6/site-packages/nilearn/reporting/html_document.py:60: UserWarning: It seems you have created more than 10 nilearn views. As each view uses dozens of megabytes of RAM, you might want to delete some of them.
  MAX_IMG_VIEWS_BEFORE_WARNING))
Out[33]:
In [34]:
COND_brain_vec = COND.SZ[atlas_vec]
COND_brain_img = masker.inverse_transform(COND_brain_vec)

nlp.view_img(COND_brain_img, title="SZ CER CRUS II L", cmap=plt.cm.seismic, vmax=0.5, threshold=0.1)

/Users/Clara/anaconda3/lib/python3.6/site-packages/nilearn/reporting/html_document.py:60: UserWarning: It seems you have created more than 10 nilearn views. As each view uses dozens of megabytes of RAM, you might want to delete some of them.
  MAX_IMG_VIEWS_BEFORE_WARNING))
Out[34]:
In [35]:
COND_brain_vec = COND.BIP[atlas_vec]
COND_brain_img = masker.inverse_transform(COND_brain_vec)

nlp.view_img(COND_brain_img, title="BIP CER CRUS II L", cmap=plt.cm.seismic, vmax=0.5, threshold=0.1)

/Users/Clara/anaconda3/lib/python3.6/site-packages/nilearn/reporting/html_document.py:60: UserWarning: It seems you have created more than 10 nilearn views. As each view uses dozens of megabytes of RAM, you might want to delete some of them.
  MAX_IMG_VIEWS_BEFORE_WARNING))
Out[35]:

CRUS II - right

In [36]:
COND_p = root_p / 'R_CERCR2_seed_minibrain.csv'
COND=pd.read_csv(COND_p, sep=',')
In [37]:
COND_brain_vec = COND.ASD[atlas_vec]
COND_brain_img = masker.inverse_transform(COND_brain_vec)

nlp.view_img(COND_brain_img, title="ASD CER CRUS II R", cmap=plt.cm.seismic, vmax=0.5, threshold=0.1)

/Users/Clara/anaconda3/lib/python3.6/site-packages/nilearn/reporting/html_document.py:60: UserWarning: It seems you have created more than 10 nilearn views. As each view uses dozens of megabytes of RAM, you might want to delete some of them.
  MAX_IMG_VIEWS_BEFORE_WARNING))
Out[37]:
In [38]:
COND_brain_vec = COND.SZ[atlas_vec]
COND_brain_img = masker.inverse_transform(COND_brain_vec)

nlp.view_img(COND_brain_img, title="SZ CER CRUS II R", cmap=plt.cm.seismic, vmax=0.5, threshold=0.1)

/Users/Clara/anaconda3/lib/python3.6/site-packages/nilearn/reporting/html_document.py:60: UserWarning: It seems you have created more than 10 nilearn views. As each view uses dozens of megabytes of RAM, you might want to delete some of them.
  MAX_IMG_VIEWS_BEFORE_WARNING))
Out[38]:
In [39]:
COND_brain_vec = COND.BIP[atlas_vec]
COND_brain_img = masker.inverse_transform(COND_brain_vec)

nlp.view_img(COND_brain_img, title="BIP CER CRUS II R", cmap=plt.cm.seismic, vmax=0.5, threshold=0.1)

/Users/Clara/anaconda3/lib/python3.6/site-packages/nilearn/reporting/html_document.py:60: UserWarning: It seems you have created more than 10 nilearn views. As each view uses dozens of megabytes of RAM, you might want to delete some of them.
  MAX_IMG_VIEWS_BEFORE_WARNING))
Out[39]: